class_docstr: Encoder object recast into an API that is compatible with
  Pipeline().
class_docstr_tok: ["Encoder","object","recast","into","an","API","that","is","compatible","with","Pipeline","(",")","."]
code: def fit(self, *args):
      return self
  
file_path: interpret-text/python/interpret_text/experimental/classical.py
imports: import numpy
  from sklearn.model_selection import GridSearchCV
  from sklearn.linear_model import LogisticRegression
  from sklearn.pipeline import Pipeline
  from interpret_text.experimental.common.base_explainer import _validate_X
  from interpret_text.experimental.common.utils_classical import BOWEncoder
  from interpret_text.experimental.common.constants import ExplainerParams
  from interpret_text.experimental.explanation import _create_local_explanation
label_desc: Use image node_id 3 for calling the Encoder obj's underlying member method code with example usage: obj.fit() and returns: self